export.py

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse
import os

import paddle
import yaml
from paddle.static import InputSpec
from paddle3d.apis.config import Config

def parse_args():
    parser = argparse.ArgumentParser(description='Model export.')
    # params of training
    parser.add_argument(
        "--config",
        dest="cfg",
        help="The config file.",
        default=None,
        type=str,
        required=True)
    parser.add_argument(
        '--save_dir',
        dest='save_dir',
        help='The directory for saving the exported model',
        type=str,
        default='./output')
    parser.add_argument(
        '--model_path',
        dest='model_path',
        help='The path of model for export',
        type=str,
        default=None)
    parser.add_argument(
        "--input_shape",
        nargs='+',
        help="Export the model with fixed input shape, such as 1 3 1024 1024.",
        type=int,
        default=None)

    return parser.parse_args()

def main(args):
    cfg = Config(path=args.cfg)
    net = cfg.model

    if args.model_path:
        para_state_dict = paddle.load(args.model_path)
        net.set_dict(para_state_dict)
        
    net.eval()
    input_spec = [{
                "images": InputSpec(
                    shape=[None,3,None,None], name="images"),
                "trans_lidar_to_cam": InputSpec(
                    shape=[None,4,4], name='trans_lidar_to_cam'),
                "trans_cam_to_img": InputSpec(
                    shape=[None,3,4], name='trans_cam_to_img'),
                }]
                
    
    static_model = paddle.jit.to_static(
                net, input_spec=input_spec)
    
    save_path = os.path.join(args.save_dir, 'model')
    paddle.jit.save(static_model, save_path, input_spec=[input_spec])

if __name__ == '__main__':
    args = parse_args()
    main(args)